{
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   "execution_count": 4,
   "metadata": {},
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       "<script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script><script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window._Plotly) {require(['plotly'],function(plotly) {window._Plotly=plotly;});}</script>"
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       "<script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script><script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window._Plotly) {require(['plotly'],function(plotly) {window._Plotly=plotly;});}</script>"
      ]
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     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly\n",
    "import plotly.graph_objs as go\n",
    "import plotly.figure_factory as ff\n",
    "import numpy as np\n",
    "plotly.offline.init_notebook_mode(connected=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basic Histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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{\"title\": \"Count\"}}, {\"showLink\": true, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\"})});</script><script type=\"text/javascript\">window.addEventListener(\"resize\", function(){window._Plotly.Plots.resize(document.getElementById(\"96966fb6-525b-4838-af2b-097ccedf02da\"));});</script>"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.random.randn(500)\n",
    "data = [go.Histogram(\n",
    "    x=x,\n",
    "    # 是否进行标准化\n",
    "    histnorm='probability',\n",
    "    # 是否进行累计显示\n",
    "    cumulative=dict(enabled=False),\n",
    ")]\n",
    "layout = go.Layout(\n",
    "    title='Sampled Results',\n",
    "    xaxis=dict(title='Value'),\n",
    "    yaxis=dict(title='Count'),\n",
    "    bargap=0.2,\n",
    ")\n",
    "fig = go.Figure(data=data, layout=layout)\n",
    "plotly.offline.iplot(fig, filename='basic histogram')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basic Distplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x1 = np.random.randn(200)-2  \n",
    "x2 = np.random.randn(200)  \n",
    "x3 = np.random.randn(200)+2  \n",
    "x4 = np.random.randn(200)+4  \n",
    "colors = ['#A56CC1', '#A6ACEC', '#63F5EF', '#43AB32']\n",
    "\n",
    "hist_data = [x1, x2, x3, x4]\n",
    "group_labels = ['Group 1', 'Group 2', 'Group 3', 'Group 4']\n",
    "\n",
    "fig = ff.create_distplot(\n",
    "    hist_data, group_labels, \n",
    "    bin_size=.2, \n",
    "    colors=colors,\n",
    "    # 设置显示什么\n",
    "    show_hist=True, \n",
    "    show_curve=True, \n",
    "    show_rug=True)\n",
    "plotly.offline.iplot(fig)"
   ]
  }
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